IAM for Bolt AI agent credential access
Bolt by StackBlitz can generate and execute a browser-based application workflow that spans source code, database configuration, payment setup, and deployment. The resulting project may be short-lived, but the credentials used to test it are not harmless: a service-role database key, a live Stripe secret, or a broad GitHub token can outlive the build and be copied into generated files, browser tooling, or logs. Treat Bolt as a distinct workload with a known project, environment, and approved service set—not as a substitute for a developer account with accumulated access.
Why does Bolt need scoped credential management?
Bolt can scaffold code that calls real APIs before a team has completed its usual review cycle. The service provider still defines the effective capability boundary: a Stripe key's mode and permissions, a Supabase project's key type and RLS policies, a GitHub token's repository selection, and a Vercel token's project scope. Gazebo complements those controls by making credential delivery conditional on the current Bolt build profile. This makes it possible to stop one build, inspect what it requested, and keep unrelated builds or production systems running without a broad credential rotation.
How Gazebo works with Bolt
- 1
Choose provider credentials for the exact Bolt project and phase: test-mode billing, one Supabase project, a repository-limited GitHub identity, and a preview deployment path where possible.
- 2
Create a named Bolt profile for the build and environment. Separate discovery or read-only work from a write-capable integration or release workflow rather than broadening one profile over time.
- 3
Configure the approved credential path through Gazebo and keep raw service values out of the prompt, browser storage, project exports, and generated environment files.
- 4
Bolt requests a mapped credential only when an integration needs it. Gazebo evaluates the profile and records the identity, service, and decision before delivery.
- 5
Review access history with the generated code, provider activity, and deployment result. Revoke the profile when the build ends, and rotate a provider credential if it may have been exposed outside the intended runtime.
What this looks like in practice
Test integrations without production keys
Give Bolt a restricted Stripe test-mode credential during scaffolding, and validate product IDs, webhook handling, idempotency, and error paths before any live release. A successful test checkout is not evidence that the generated code should receive customer-data, refund, or production-webhook authority.
Supabase project isolation
Assign each Bolt project its own Supabase profile and keep the target project explicit. Use a client-facing key for user-path testing where possible; reserve service-role access for a separately approved server-side task. This prevents a browser-based experiment from inheriting database authority from another build in the same organisation.
Full credential audit trail
Use Gazebo's record to establish which Bolt build requested which credential and when, then correlate it with the provider's API, database, deployment, and repository logs to understand the action that followed. Retrieval proves access was granted; it does not by itself prove that a payment, query, commit, or deployment succeeded.
Set up Gazebo for Bolt
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Further reading
AI Agent Security Checklist: Cursor, Replit, and Copilot
Six things to do before shipping AI agents to production — scoped credentials, approval gates, audit logs, and a revocation path that doesn't take down everything else.
Why Environment Variables Are Insecure for AI Agents
Environment variables feel like a secure way to pass credentials to AI agents. They're not. Here's why the process environment is a shared bus, not a secrets store — and what to do instead.
Why AI Agents Shouldn't Share API Keys
The blast radius problem with shared credentials — and how to apply least privilege to every AI agent you run.
What Happens When You Paste an API Key Into an AI Agent's Prompt
It works — that's the problem. When you paste an API key into an agent's prompt, the key enters conversation logs, model context, and provider infrastructure you don't control. Here's where it actually goes.